In shared memory multiprocessor architectures, threads can be
used to implement parallelism. Historically, hardware vendors have
implemented their own proprietary versions of threads, making portability a
concern for software developers. For UNIX systems, a standardized C
language threads programming interface has been specified by the IEEE
POSIX 1003.1c standard. Implementations that adhere to this standard are
referred to as POSIX threads, or Pthreads.

The tutorial begins with an introduction to concepts, motivations, and design
considerations for using Pthreads. Each of the three major classes of
routines in the Pthreads API are then covered: Thread Management, Mutex
Variables, and Condition Variables. Example codes are used throughout to
demonstrate how to use most of the Pthreads routines needed by a new Pthreads
programmer. The tutorial concludes with a discussion of LLNL specifics and
how to mix MPI with pthreads. A lab
exercise, with numerous example codes (C Language) is also included.

Level/Prerequisites: This tutorial is ideal for those who are new to parallel programming with pthreads. A basic understanding of parallel programming in C is required. For those who are unfamiliar with Parallel Programming in general, the material covered in
EC3500: Introduction to Parallel
Computing would be helpful.

Pthreads Overview

What is a Thread?

Technically, a thread is defined as an independent stream of
instructions that can be scheduled to run as such by the
operating system. But what does this mean?

To the software developer, the concept of a "procedure" that runs
independently from its main program may best describe a thread.

To go one step further, imagine a main program (a.out) that contains
a number of procedures. Then imagine all of these procedures being
able to be scheduled to run simultaneously and/or independently by
the operating system. That would describe a "multi-threaded" program.

How is this accomplished?

Before understanding a thread, one first needs to understand a UNIX process.
A process is created by the operating system, and requires a fair amount
of "overhead". Processes contain information about program
resources and program execution state, including:

Threads use and exist within these process resources, yet are able to
be scheduled by the operating system and run as independent entities
largely because they duplicate only the bare essential resources that
enable them to exist as executable code.

This independent flow of control is accomplished because a thread
maintains its own:

Stack pointer

Registers

Scheduling properties (such as policy or priority)

Set of pending and blocked signals

Thread specific data.

So, in summary, in the UNIX environment a thread:

Exists within a process and uses the process resources

Has its own independent flow of control as long as
its parent process exists and the OS supports it

Duplicates only the essential resources it needs to be independently
schedulable

May share the process resources with other threads that act
equally independently (and dependently)

Dies if the parent process dies - or something similar

Is "lightweight" because most of the overhead has already been
accomplished through the creation of its process.

Because threads within the same process share resources:

Changes made by one thread to shared system resources (such as closing
a file) will be seen by all other threads.

Two pointers having the same value point to the same data.

Reading and writing to the same memory locations is possible, and
therefore requires explicit synchronization by the programmer.

Pthreads Overview

What are Pthreads?

Historically, hardware vendors have implemented their own proprietary
versions of threads. These implementations differed substantially from
each other making it difficult for programmers to develop portable
threaded applications.

In order to take full advantage of the capabilities provided by threads,
a standardized programming interface was required.

For UNIX systems, this interface has been specified by the IEEE
POSIX 1003.1c standard (1995).

Implementations adhering to this standard are referred to as POSIX
threads, or Pthreads.

Most hardware vendors now offer Pthreads in addition to their
proprietary API's.

The POSIX standard has continued to evolve and undergo revisions,
including the Pthreads specification.

Pthreads are defined as a set of C language programming types and
procedure calls, implemented with a pthread.h header/include file
and a thread library - though this library may be part of another
library, such as libc, in some implementations.

Pthreads Overview

Why Pthreads?

Light Weight:

When compared to the cost of creating and managing a process, a thread
can be created with much less operating system overhead. Managing threads
requires fewer system resources than managing processes.

For example, the following table compares timing results
for the fork() subroutine and
the pthread_create() subroutine. Timings reflect
50,000 process/thread creations, were performed with the time
utility, and units are in seconds, no optimization flags.

Note: don't expect the sytem and user times to add up to real time,
because these are SMP systems with multiple CPUs/cores working on the problem
at the same time. At best, these are approximations run on local machines,
past and present.

The primary motivation for considering the use of Pthreads in a high
performance computing environment is to achieve optimum performance.
In particular, if an application is using MPI for on-node communications,
there is a potential that performance could be improved by using Pthreads
instead.

For Pthreads there is no intermediate memory copy required because
threads share the same address space within a single process. There
is no data transfer, per se. It can be as efficient as simply passing
a pointer.

In the worst case scenario, Pthread communications become more of a
cache-to-CPU or memory-to-CPU bandwidth issue. These speeds are much
higher than MPI shared memory communications.

For example: some local comparisons, past and present, are shown below:

Platform

MPI Shared Memory Bandwidth(GB/sec)

Pthreads Worst CaseMemory-to-CPU Bandwidth (GB/sec)

Intel 2.6 GHz Xeon E5-2670

4.5

51.2

Intel 2.8 GHz Xeon 5660

5.6

32

AMD 2.3 GHz Opteron

1.8

5.3

AMD 2.4 GHz Opteron

1.2

5.3

IBM 1.9 GHz POWER5 p5-575

4.1

16

IBM 1.5 GHz POWER4

2.1

4

Intel 2.4 GHz Xeon

0.3

4.3

Intel 1.4 GHz Itanium 2

1.8

6.4

Other Common Reasons:

Threaded applications offer potential performance gains and practical
advantages over non-threaded applications in several other ways:

Overlapping CPU work with I/O: For example, a program may have
sections where it is performing a long I/O operation. While one
thread is waiting for an I/O system call to complete, CPU intensive
work can be performed by other threads.

Priority/real-time scheduling: tasks which are more important can
be scheduled to supersede or interrupt lower priority tasks.

Asynchronous event handling: tasks which service events of indeterminate
frequency and duration can be interleaved. For example, a web server
can both transfer data from previous requests and manage the arrival
of new requests.

A perfect example is the typical web browser, where many interleaved
tasks can be happening at the same time, and where tasks can vary in
priority.

Another good example is a modern operating system, which makes extensive
use of threads. A screenshot of the MS Windows OS and applications using
threads is shown below.

In general though, in order for a program to take advantage of Pthreads, it
must be able to be organized into discrete, independent tasks which can
execute concurrently. For example, if routine1 and routine2 can be
interchanged, interleaved and/or overlapped in real time, they are candidates
for threading.

Programs having the following characteristics may be well suited for pthreads:

Work that can be executed, or data that can be operated on, by multiple
tasks simultaneously:

Block for potentially long I/O waits

Use many CPU cycles in some places but not others

Must respond to asynchronous events

Some work is more important than other work (priority interrupts)

Several common models for threaded programs exist:

Manager/worker:
a single thread, the manager assigns work
to other threads, the workers. Typically, the manager handles
all input and parcels out work to the other tasks. At least two
forms of the manager/worker model are common: static worker pool and
dynamic worker pool.

Pipeline:
a task is broken into a series of suboperations,
each of which is handled in series, but concurrently, by a different
thread. An automobile assembly line best describes this model.

Peer:
similar to the manager/worker model, but after the main
thread creates other threads, it participates in the work.

For example, suppose that your application creates several threads, each
of which makes a call to the same library routine:

This library routine accesses/modifies a global structure or location
in memory.

As each thread calls this routine it is possible that
they may try to modify this global structure/memory location at the
same time.

If the routine does not employ some sort of synchronization
constructs to prevent data corruption, then it is not thread-safe.

The implication to users of external library routines is that if you
aren't 100% certain the routine is thread-safe, then you take your
chances with problems that could arise.

Recommendation: Be careful if your application uses libraries or other objects
that don't explicitly guarantee thread-safeness. When in doubt,
assume that they are not thread-safe until proven otherwise. This can be done by
"serializing" the calls to the uncertain routine, etc.

Thread Limits:

Although the Pthreads API is an ANSI/IEEE standard, implementations can, and
usually do, vary in ways not specified by the standard.

Because of this, a program that runs fine on one platform, may fail or produce
wrong results on another platform.

For example, the maximum number of threads permitted, and the default thread
stack size are two important limits to consider when designing your program.

Several thread limits are discussed in more detail later in this tutorial.

The Pthreads API

The original Pthreads API was defined in the ANSI/IEEE POSIX 1003.1 - 1995
standard. The POSIX standard has continued to evolve and undergo revisions,
including the Pthreads specification.

Copies of the standard can be purchased from IEEE or downloaded for free
from other sites online.

The subroutines which comprise the Pthreads API can be informally grouped
into four major groups:

Mutexes: Routines that deal with
synchronization, called a "mutex", which is an abbreviation
for "mutual exclusion". Mutex functions provide for creating,
destroying, locking and unlocking mutexes.
These are supplemented by mutex attribute functions that
set or modify attributes associated with mutexes.

Condition variables: Routines that address
communications between threads that share a mutex. Based upon
programmer specified
conditions. This group includes functions to create, destroy,
wait and signal based upon specified variable values.
Functions to set/query condition variable attributes are also included.

Synchronization: Routines that manage read/write locks and
barriers.

Naming conventions: All identifiers in the threads library begin with
pthread_. Some examples are shown below.

Routine Prefix

Functional Group

pthread_

Threads themselves and miscellaneous subroutines

pthread_attr_

Thread attributes objects

pthread_mutex_

Mutexes

pthread_mutexattr_

Mutex attributes objects.

pthread_cond_

Condition variables

pthread_condattr_

Condition attributes objects

pthread_key_

Thread-specific data keys

pthread_rwlock_

Read/write locks

pthread_barrier_

Synchronization barriers

The concept of opaque objects pervades the design of the API.
The basic calls work to create or modify opaque objects - the
opaque objects can be modified by calls to attribute functions,
which deal with opaque attributes.

The Pthreads API contains around 100 subroutines. This tutorial will
focus on a subset of these - specifically, those which are most likely
to be immediately useful to the beginning Pthreads programmer.

For portability, the pthread.h header file should be included in
each source file using the Pthreads library.

The current POSIX standard is defined only for the C language.
Fortran programmers can use wrappers around C function calls.
Some Fortran compilers may provide a Fortran pthreads API.

A number of excellent books about Pthreads are available. Several of
these are listed in the References
section of this tutorial.

Compiling Threaded Programs

Several examples of compile commands used for pthreads codes are
listed in the table below.

Creating and Terminating Threads

Initially, your main() program comprises a single, default
thread. All other threads must be explicitly created by the programmer.

pthread_create creates a new thread and makes it executable.
This routine can be called any number of times from anywhere within your
code.

pthread_create arguments:

thread: An opaque, unique identifier for the new thread
returned by the subroutine.

attr: An opaque attribute object that may be used to set
thread attributes. You can specify a thread attributes object, or
NULL for the default values.

start_routine: the C routine that the thread will
execute once it is created.

arg: A single argument that may be passed to
start_routine. It must be passed by reference as a pointer
cast of type void. NULL may be used if no argument is to be passed.

The maximum number of threads that may be created by a process is
implementation dependent. Programs that attempt to exceed the limit can
fail or produce wrong results.

Querying and setting your implementation's thread limit - Linux example shown.
Demonstrates querying the default (soft) limits and then setting the
maximum number of processes (including threads) to the hard limit. Then
verifying that the limit has been overridden.

Once created, threads are peers, and may create other threads. There is no
implied hierarchy or dependency between threads.

Thread Attributes:

By default, a thread is created with certain attributes. Some of these
attributes can be changed by the programmer via the thread attribute
object.

pthread_attr_init and pthread_attr_destroy are used to
initialize/destroy the thread attribute object.

Other routines are then used to query/set specific attributes in the
thread attribute object. Attributes include:

Detached or joinable state

Scheduling inheritance

Scheduling policy

Scheduling parameters

Scheduling contention scope

Stack size

Stack address

Stack guard (overflow) size

Some of these attributes will be discussed later.

Thread Binding and Scheduling:

Question: After a thread has been created, how do you know a)when it
will be scheduled to run by the operating system, and b)which processor/core
it will run on?

The Pthreads API provides several routines that may be used to specify how
threads are scheduled for execution. For example, threads can be scheduled
to run FIFO (first-in first-out), RR (round-robin) or OTHER (operating system
determines). It also provides the ability to set a thread's scheduling priority
value.

These topics are not covered here, however a good overview of "how things work"
under Linux can be found in the
sched_setscheduler
man page.

The Pthreads API does not provide routines for binding threads to specific
cpus/cores. However, local implementations may include this functionality
- such as providing the non-standard
pthread_setaffinity_np routine. Note that "_np" in the name
stands for "non-portable".

Also, the local operating system may provide a way to do this.
For example, Linux provides the
sched_setaffinity
routine.

Terminating Threads & pthread_exit():

There are several ways in which a thread may be terminated:

The thread returns normally from its starting routine. Its work is done.

The thread makes a call to the pthread_exit subroutine - whether
its work is done or not.

The thread is canceled by another thread via the pthread_cancel
routine.

The entire process is terminated due to making a call to either the
exec() or exit()

The pthread_exit() routine allows the programmer to specify an
optional termination status parameter. This optional parameter is
typically returned to threads "joining" the terminated thread (covered
later).

In subroutines that execute to completion normally, you can
often dispense with calling pthread_exit() - unless, of course,
you want to pass the optional status code back.

Cleanup: the pthread_exit() routine does not close files; any
files opened inside the thread will remain open after the thread is
terminated.

Discussion on calling pthread_exit() from main():

There is a definite problem if main() finishes before the threads
it spawned if you don't call pthread_exit() explicitly. All of the
threads it created will terminate because main() is done and no longer
exists to support the threads.

By having main() explicitly call pthread_exit() as the last thing
it does, main() will block and be kept alive to support the threads it
created until they are done.

Example: Pthread Creation and Termination

This simple example code creates 5 threads with the
pthread_create() routine. Each thread prints a "Hello World!"
message, and then terminates with a call to pthread_exit().

Passing Arguments to Threads

The pthread_create() routine permits the programmer to pass
one argument to the thread start routine. For cases where multiple
arguments must be passed, this limitation is easily overcome by creating
a structure which contains all of the arguments, and then passing a
pointer to that structure in the pthread_create() routine.

All arguments must be passed by reference and cast to (void *).

Question: How can you safely pass data to newly created threads, given
their non-deterministic start-up and scheduling?

Example 1 - Thread Argument Passing

This code fragment demonstrates how to pass a simple integer
to each thread. The calling thread uses a unique data structure for
each thread, insuring that each thread's argument remains intact
throughout the program.

This example performs argument passing incorrectly. It passes the address
of variable t, which is shared memory space and visible to all threads.
As the loop iterates, the value of this memory location changes, possibly
before the created threads can access it.

Joining and Detaching Threads

"Joining" is one way to accomplish synchronization between threads. For
example:

The pthread_join() subroutine blocks the calling thread until the
specified threadid thread terminates.

The programmer is able to obtain the target thread's termination
return status if it was specified in the target thread's
call to pthread_exit().

A joining thread can match one pthread_join() call. It is a
logical error to attempt multiple joins on the same thread.

Two other synchronization methods, mutexes and condition variables, will
be discussed later.

Joinable or Not?

When a thread is created, one of its attributes defines whether
it is joinable or detached. Only threads that are created as joinable
can be joined. If a thread is created as detached, it can never be joined.

The final draft of the POSIX standard specifies that threads should be
created as joinable.

To explicitly create a thread as joinable or detached, the
attr argument in the pthread_create() routine
is used. The typical 4 step process is:

Declare a pthread attribute variable of the pthread_attr_t
data type

Initialize the attribute variable with
pthread_attr_init()

Set the attribute detached status with
pthread_attr_setdetachstate()

When done, free library resources used by the attribute with
pthread_attr_destroy()

Detaching:

The pthread_detach() routine can be used to explicitly detach
a thread even though it was created as joinable.

There is no converse routine.

Recommendations:

If a thread requires joining, consider explicitly creating it as
joinable. This provides portability as not all implementations
may create threads as joinable by default.

If you know in advance that a thread will never need to join with
another thread, consider creating it in a detached state. Some
system resources may be able to be freed.

Example: Pthread Joining

This example demonstrates how to "wait" for thread completions by using
the Pthread join routine.

Since some implementations of Pthreads may
not create threads in a joinable state, the threads in this
example are explicitly created in a joinable state so that they can
be joined later.

Miscellaneous Routines

pthread_self returns the unique, system
assigned thread ID of the calling thread.

pthread_equal compares two thread IDs. If the
two IDs are different 0 is returned, otherwise a non-zero value is
returned.

Note that for both of these routines, the thread identifier objects are
opaque and can not be easily inspected. Because thread IDs are opaque
objects, the C language equivalence operator == should not be
used to compare two thread IDs against each other, or to compare a
single thread ID against another value.

pthread_once executes the init_routine exactly once in
a process. The first call to this routine by any thread in the process
executes the given init_routine, without parameters.
Any subsequent call will have no effect.

The init_routine routine is typically an initialization routine.

The once_control parameter is a synchronization control structure
that requires initialization prior to calling pthread_once.
For example:

Overview

Mutex is an abbreviation for "mutual exclusion". Mutex variables are one
of the primary means of implementing thread synchronization and for
protecting shared data when multiple writes occur.

A mutex variable acts like a "lock" protecting access to a shared
data resource. The basic concept of a mutex as used in Pthreads is
that only one thread can lock (or own) a mutex variable at any given
time. Thus, even if several threads try to lock a mutex only one thread
will be successful. No other thread can own that mutex until
the owning thread unlocks that mutex. Threads must "take turns" accessing
protected data.

Mutexes can be used to prevent "race" conditions. An example of
a race condition involving a bank transaction is shown below:

Thread 1

Thread 2

Balance

Read balance: $1000

$1000

Read balance: $1000

$1000

Deposit $200

$1000

Deposit $200

$1000

Update balance $1000+$200

$1200

Update balance $1000+$200

$1200

In the above example, a mutex should be used to lock the "Balance"
while a thread is using this shared data resource.

Very often the action performed by a thread owning a mutex
is the updating of global variables. This is a safe way to
ensure that when several threads update the same variable,
the final value is the same as what it would be if only one
thread performed the update. The variables being updated belong
to a "critical section".

A typical sequence in the use of a mutex is as follows:

Create and initialize a mutex variable

Several threads attempt to lock the mutex

Only one succeeds and that thread owns the mutex

The owner thread performs some set of actions

The owner unlocks the mutex

Another thread acquires the mutex and repeats the process

Finally the mutex is destroyed

When several threads compete for a mutex, the losers block
at that call - an unblocking call is available with "trylock"
instead of the "lock" call.

When protecting shared data, it is the programmer's responsibility
to make sure every thread that needs to use a mutex does so. For
example, if 4 threads are updating the same data, but only one
uses a mutex, the data can still be corrupted.

The attr object is used to establish properties for the mutex
object, and must be of type pthread_mutexattr_t if used
(may be specified as NULL to accept defaults).
The Pthreads standard defines three optional mutex attributes:

Protocol: Specifies the protocol used to prevent priority inversions
for a mutex.

Prioceiling: Specifies the priority ceiling of a mutex.

Process-shared: Specifies the process sharing of a mutex.

Note that not all implementations may provide the three optional mutex
attributes.

The pthread_mutexattr_init() and
pthread_mutexattr_destroy() routines are used to create and
destroy mutex attribute objects respectively.

pthread_mutex_destroy() should be used to free a mutex object
which is no longer needed.

Mutex Variables

Locking and Unlocking Mutexes

The pthread_mutex_lock() routine is used by a thread to
acquire a lock on the specified mutex variable. If the mutex
is already locked by another thread, this call will block the calling
thread until the mutex is unlocked.

pthread_mutex_trylock() will attempt to lock a mutex. However,
if the mutex is already locked, the routine will return immediately
with a "busy" error code. This routine may be useful in preventing
deadlock conditions, as in a priority-inversion situation.

pthread_mutex_unlock() will unlock a mutex if called by the
owning thread. Calling this routine is required after a thread has
completed its use of protected data if other threads are to acquire the
mutex for their work with the protected data. An error will be returned if:

If the mutex was already unlocked

If the mutex is owned by another thread

There is nothing "magical" about mutexes...in fact they are akin to
a "gentlemen's agreement" between participating threads. It is up to
the code writer to insure that the necessary threads all make the
the mutex lock and unlock calls correctly.
The following scenario demonstrates a logical error:

#include &LT;pthread.h&GT;
#include &LT;stdio.h&GT;
#include &LT;stdlib.h&GT;
/*
The following structure contains the necessary information
to allow the function "dotprod" to access its input data and
place its output into the structure.
*/
typedef struct
{
double *a;
double *b;
double sum;
int veclen;
} DOTDATA;
/* Define globally accessible variables and a mutex */
#define NUMTHRDS 4
#define VECLEN 100
DOTDATA dotstr;
pthread_t callThd[NUMTHRDS];pthread_mutex_t mutexsum;/*
The function dotprod is activated when the thread is created.
All input to this routine is obtained from a structure
of type DOTDATA and all output from this function is written into
this structure. The benefit of this approach is apparent for the
multi-threaded program: when a thread is created we pass a single
argument to the activated function - typically this argument
is a thread number. All the other information required by the
function is accessed from the globally accessible structure.
*/
void *dotprod(void *arg)
{
/* Define and use local variables for convenience */
int i, start, end, len ;
long offset;
double mysum, *x, *y;
offset = (long)arg;
len = dotstr.veclen;
start = offset*len;
end = start + len;
x = dotstr.a;
y = dotstr.b;
/*
Perform the dot product and assign result
to the appropriate variable in the structure.
*/
mysum = 0;
for (i=start; i&LT;end ; i++)
{
mysum += (x[i] * y[i]);
}
/*
Lock a mutex prior to updating the value in the shared
structure, and unlock it upon updating.
*/pthread_mutex_lock (&mutexsum);
dotstr.sum += mysum;
pthread_mutex_unlock (&mutexsum);pthread_exit((void*) 0);
}
/*
The main program creates threads which do all the work and then
print out result upon completion. Before creating the threads,
the input data is created. Since all threads update a shared structure,
we need a mutex for mutual exclusion. The main thread needs to wait for
all threads to complete, it waits for each one of the threads. We specify
a thread attribute value that allow the main thread to join with the
threads it creates. Note also that we free up handles when they are
no longer needed.
*/
int main (int argc, char *argv[])
{
long i;
double *a, *b;
void *status;
pthread_attr_t attr;/* Assign storage and initialize values */
a = (double*) malloc (NUMTHRDS*VECLEN*sizeof(double));
b = (double*) malloc (NUMTHRDS*VECLEN*sizeof(double));
for (i=0; i&LT;VECLEN*NUMTHRDS; i++)
{
a[i]=1.0;
b[i]=a[i];
}
dotstr.veclen = VECLEN;
dotstr.a = a;
dotstr.b = b;
dotstr.sum=0;
pthread_mutex_init(&mutexsum, NULL);/* Create threads to perform the dotproduct */pthread_attr_init(&attr);pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_JOINABLE);
for(i=0; i&LT;NUMTHRDS; i++)
{
/*
Each thread works on a different set of data. The offset is specified
by 'i'. The size of the data for each thread is indicated by VECLEN.
*/pthread_create(&callThd[i], &attr, dotprod, (void *)i);
}
pthread_attr_destroy(&attr);/* Wait on the other threads */
for(i=0; i&LT;NUMTHRDS; i++)
{
pthread_join(callThd[i], &status);
}
/* After joining, print out the results and cleanup */
printf ("Sum = %f \n", dotstr.sum);
free (a);
free (b);
pthread_mutex_destroy(&mutexsum);pthread_exit(NULL);
}

Serial versionPthreads version

Condition Variables

Overview

Condition variables provide yet another way for threads to synchronize.
While mutexes implement synchronization by controlling thread access to
data, condition variables allow threads to synchronize based upon the
actual value of data.

Without condition variables, the programmer would need to have
threads continually polling (possibly in a critical section), to check
if the condition is met. This can be very resource consuming since
the thread would be continuously busy in this activity. A condition
variable is a way to achieve the same goal without polling.

A condition variable is always used in conjunction with a mutex lock.

A representative sequence for using condition variables is shown below.

Do work up to the point where a certain condition must
occur (such as "count" must reach a specified value)

Lock associated mutex and check value of a global variable

Call pthread_cond_wait() to perform a blocking wait for
signal from Thread-B.
Note that a call to pthread_cond_wait() automatically and
atomically unlocks the associated mutex variable so that it can be
used by Thread-B.

When signalled, wake up. Mutex is automatically and atomically locked.

Explicitly unlock mutex

Continue

Thread B

Do work

Lock associated mutex

Change the value of the global variable that Thread-A is waiting upon.

Check value of the global Thread-A wait variable. If it fulfills
the desired condition, signal Thread-A.

Creating and Destroying Condition Variables

Condition variables must be declared with type pthread_cond_t,
and must be initialized before they can be used. There are two ways
to initialize a condition variable:

Statically, when it is declared. For example:
pthread_cond_t myconvar = PTHREAD_COND_INITIALIZER;

Dynamically, with the pthread_cond_init() routine.
The ID of the created condition variable is returned to the calling
thread through the condition parameter.
This method permits setting condition variable object attributes,
attr.

The optional attr object is used to set condition variable
attributes. There is only one attribute defined for condition variables:
process-shared, which allows the condition variable to be seen by
threads in other processes. The attribute object, if used, must be
of type pthread_condattr_t (may be specified as NULL to accept
defaults).

Note that not all implementations may provide the process-shared attribute.

The pthread_condattr_init() and
pthread_condattr_destroy() routines are used to create and
destroy condition variable attribute objects.

pthread_cond_destroy() should be used to free a condition
variable that is no longer needed.

Condition Variables

Waiting and Signaling on Condition Variables

pthread_cond_wait() blocks the calling thread until the
specified condition is signalled. This routine should be called
while mutex is locked, and it will automatically release the
mutex while it waits.
After signal is received and thread is awakened, mutex will be
automatically locked for use by the thread. The programmer is then
responsible for unlocking mutex when the thread is finished with it.

Recommendation: Using a WHILE loop instead of an IF statement
(see watch_count routine in example below) to check the waited for condition
can help deal with several potential problems, such as:

If several threads are waiting for the same wake up signal, they will
take turns acquiring the mutex, and any one of them can then modify the
condition they all waited for.

If the thread received the signal in error due to a program bug

The Pthreads library is permitted to issue spurious wake ups to a waiting
thread without violating the standard.

The pthread_cond_signal() routine is used to signal (or wake up)
another thread which is waiting on the condition variable. It should
be called after mutex is locked, and must unlock mutex in
order for pthread_cond_wait() routine to complete.

The pthread_cond_broadcast() routine should be used instead of
pthread_cond_signal() if more than one thread is in a blocking
wait state.

It is a logical error to call pthread_cond_signal() before
calling pthread_cond_wait().

Proper locking and unlocking of the associated mutex variable is essential
when using these routines. For example:

Failing to lock the mutex before calling
pthread_cond_wait() may cause it NOT to block.

Failing to unlock the mutex after calling pthread_cond_signal()
may not allow a matching pthread_cond_wait() routine to
complete (it will remain blocked).

Example: Using Condition Variables

This simple example code demonstrates the use of several Pthread condition
variable routines.

The main routine creates three threads.

Two of the threads perform work and update a "count" variable.

The third thread waits until the count variable reaches a specified value.

LC's Linux clusters also provide the top command to monitor
processes on a node. If used with the -H flag,
the threads contained within a process will be visible. An example
of the top -H command is shown below. The parent
process is PID 18010 which spawned three threads, shown as PIDs 18012,
18013 and 18014.

Performance Analysis Tools:

There are a variety of performance analysis tools that can be used with
threaded programs. Searching the web will turn up a wealth of information.

Each MPI process typically creates and then manages N threads,
where N makes the best use of the available cores/node.

Finding the best value for N will vary with the platform and
your application's characteristics.

In general, there may be problems if multiple threads make MPI
calls. The program may fail or behave unexpectedly. If MPI
calls must be made from within a thread, they should be made
only by one thread.

Compiling:

Use the appropriate MPI compile command for the platform and
language of choice